Optical imaging combined with spectroscopy is commonly used for the analysis and testing of substances and materials, such as chemicals, molecules, cells, tissue, and the like, and for measurement/detection of related reactions, processes and events. These substances or processes may be arranged in units, hereto referred to collectively as “samples”, in order to facilitate handling and analysis. In order to increase speed, throughput, efficiency and to decrease cost, increasingly large numbers of samples are analyzed simultaneously in parallel, or alternatively in a high-speed serialized fashion, or a combination thereof. In many applications, a plurality of samples to be measured are prepared and organized such that they can be analyzed in an automated fashion, whereby they are placed in or on a “sample carrier”, typically in the format of an array. The sample carrier facilitates the handling, transport and processing of samples. In addition to the measurement of samples, it is increasingly important that information related to the samples and their related carriers, packaging, etc. be acquired (“read” or “measured”), as well as created, tracked, and managed in general. Such “sample information” may exist in various forms, including stored on computers, databases, lists, files, stored on integrated circuits, barcodes, or encoded onto the samples themselves. Furthermore, the said sample information may be directly readable and/or modifiable from the object to be measured, for example from sample carriers and/or from the samples themselves.
Currently the most common examples of applications from the biotechnology field include the use of microscopic analysis on microscope slides; sample analysis on microplates which can hold commonly 96, 384, or 1536 samples, multi-channel electrophoresis, multi-capillary electrophoresis, and cell-based analysis via cytometry. One strategy to increase throughput while still conforming to the microplate format is to place the samples in an “array of arrays”, whereby an increased number of samples are placed where a single sample used to be. This preserves the investment in automation systems which handle microplates. Recent advances in miniaturization include “biological chips (biochips)” and “micro-arrays” which accommodate up to hundreds of thousands of samples, whereby the physical size and volume of the samples approach the micron and sub-nanoliter ranges respectively. Further modern methods involve molecular-based sample analysis or processing on miniaturized solid substrates such as on micro-beads. The number of samples on one sample carrier is currently approaching a few million. Typically the biochemical process is monitored or a result is detected by optical measurement, primarily using fluorescence spectroscopy, chemi-luminescence, and optical absorbance and/or reflectance, whereby each and every of the mentioned samples must be analyzed. The prevalent detection method in the biotechnology field utilizes fluorescence, whereby one or more fluorescent labels are used to identify, discriminate and/or analyze the samples.
Current measurement and detection technology in this field are based on:
a) Imaging, typically using cooled scientific CCD and CID cameras. Such array sensors have the inherent advantage of parallelism—that is, they allow the simultaneous measurement of a plurality of samples arranged on a plane surface. Spectral measurement is implemented by using interchangeable optical filters. The samples are typically illuminated or excited either simultaneously, or by scanning a light source over the area.
b) Scanning systems, typically involving the scanning of a laser over the sample carrier area, with measurement using one or more optical sensors such as Photomultiplier Tubes (PMT) or Avalanche Photodiodes. Spectral measurement is implemented either by using a number (n) of interchangeable optical filters with a single sensor, implying that the area to be measured must be scanned (n) times; or a plurality of sensors, each used with an optical filter. “Confocal” optical schemes, which limit the focal plane of measurement have been used with scanning systems to increase sensitivity, and to allow a third dimension of measurement in the “Z” or focal axis.
c) Scanning confocal systems which make use of an image sensor such as a CCD (Charge Coupled Device) are known. For example, WO 95/21378 discloses a scanning single-beam confocal apparatus for DNA sequencing, using a CCD-based spectrometer. WO 00/11024 is another such example where multiple laser beam excitation is employed with confocal multiple-spectra detection by a CCD sensor. Current instrumentation have limitations on the size of the area that can be measured, the resolution that can be achieved, and the speed of measurement. Furthermore, the performance and/or consistency of measurements vary with sample position over the area to be measured. Sensitivity decreases as the area (number of samples, throughput and speed) increases.
Imaging systems based on cameras commonly are employing increasingly larger image sensors, with as small pixels as possible. This has disadvantages of lower device yields and higher cost; slower readout rates due to the larger number of pixels; optical aberrations in standard imaging optics are increasingly problematic; and the inevitable resolution limit of semiconductor technology. To perform spectroscopy, multiple images using various optical filters are acquired, leading to longer measurement time, and lower sensitivity. Laser scanning systems also suffer from the same optical imaging problems caused by aberrations as the area as well as the resolution increases. Demands increase on the precision of the mechanically scanning mirror, and reliability and robustness are issues at the relatively high scanning speeds. Sensitivity decreases due to the increased time multiplexing inherent in scanning, as well as the use of optical filters. The flatness and tilt of the surface or volume to be measured, as well as its positioning relative to the sensing system poses a problem as the area gets larger. The resulting variation in focus within the measurement area leads to location-dependent performance.